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Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which result in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement. In our study, we use ANOVA (analyses of variance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of five climate models and up to 13 hydrological models, for nine large scale river basins across the globe, under four emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies. We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge-however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.

The paper investigates climate change impacts on streamflow seasonality for a set of eleven representative large river basins covering all continents and a wide range of climatic and physiographic settings. Based on an ensemble of nine regional hydrological models driven by climate projections derived from five global circulation models under four representative concentration pathways, we analyzed the median and range of projected changes in seasonal streamflow by the end of the twenty-first century and examined the uncertainty arising from the different members of the modelling chain. Climate change impacts on the timing of seasonal streamflow were found to be small except for two basins. In many basins, we found an acceleration of the existing seasonality pattern, i.e. high-flows are projected to increase and/or low-flows are projected to decrease. In some basins the hydrologic projections indicate opposite directions of change which cancel out in the ensemble median, i.e., no robust conclusions could be drawn. In the majority of the basins, differences in projected streamflow seasonality between the low emission pathway and the high emission pathway are small with the exception of four basins. For these basins our results allow conclusions on the potential benefits (or adverse effects) of avoided GHG emissions for the seasonal streamflow regime.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

This study describes and implements an integrated, multimedia, process-based system-level approach to estimating nitrogen (N) fate and transport in large river basins. The modeling system includes the following components: (1) Community Multiscale Air Quality (CMAQ), (2) Weather Research and Forecasting Model (WRF), (3) Environmental Policy Integrated Climate (EPIC), and (4) Soil and Water Assessment Tool (SWAT). The previously developed Fertilizer Emission Scenario Tool for CMAQ (FEST-C), an advanced user interface, integrated EPIC with the WRF model and CMAQ. The FEST-C system, driven by process-based WRF weather simulations, includes atmospheric N additions to agricultural cropland and agricultural cropland contributions to ammonia emissions. This study focuses on integrating the watershed hydrology and water quality model with FEST-C system so that a full multimedia assessment on water quality in large river basins to address impacts of fertilization, meteorology, and atmospheric N deposition on water quality can be achieved. Objectives of this paper are to describe how to expand the previous effort by integrating the SWAT model with the FEST-C (CMAQ/WRF/EPIC) modeling system, as well as to demonstrate application of the Integrated Modeling System (IMS) to the Mississippi River basin (MRB) to simulate streamflow and dissolved N loadings to the Gulf of Mexico (GOM). IMS simulation results generally agree with US Geological Survey (USGS) observations/estimations; the annual simulated streamflow is 218.9 mm and USGS observation is 211.1 mm and the annual simulated dissolved N is 2.1 kg ha−1 and the USGS estimation is 2.8 kg ha−1. Integrating SWAT with the CMAQ/WRF/EPIC modeling system allows for its use within large river basins without losing EPIC's more detailed biogeochemistry processes, which will strengthen the assessment of impacts of future climate scenarios, regulatory and voluntary programs for N oxide air emissions, and land use and land management on N transport and transformation in large river basins.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

Malaria parasites use the RhopH complex for erythrocyte invasion and channel-mediated nutrient uptake. As the member proteins are unique to Plasmodium spp., how they interact and traffic through subcellular sites to serve these essential functions is unknown. We show that RhopH is synthesized as a soluble complex of CLAG3, RhopH2, and RhopH3 with 1:1:1 stoichiometry. After transfer to a new host cell, the complex crosses a vacuolar membrane surrounding the intracellular parasite and becomes integral to the erythrocyte membrane through a PTEX translocon-dependent process. We present a 2.9 Å single-particle cryo-electron microscopy structure of the trafficking complex, revealing that CLAG3 interacts with the other subunits over large surface areas. This soluble complex is tightly assembled with extensive disulfide bonding and predicted transmembrane helices shielded. We propose a large protein complex stabilized for trafficking but poised for host membrane insertion through large-scale rearrangements, paralleling smaller two-state pore-forming proteins in other organisms. Malaria is an infectious disease caused by the family of Plasmodium parasites, which pass between mosquitoes and animals to complete their life cycle. With one bite, mosquitoes can deposit up to one hundred malaria parasites into the human skin, from where they enter the bloodstream. After increasing their numbers in liver cells, the parasites hijack, invade and remodel red blood cells to create a safe space to grow and mature. This includes inserting holes in the membrane of red blood cells to take up nutrients from the bloodstream. A complex of three tightly bound RhopH proteins plays an important role in these processes. These proteins are unique to malaria parasites, and so far, it has been unclear how they collaborate to perform these specialist roles. Here, Schureck et al. have purified the RhopH complex from Plasmodium -infected human blood to determine its structure and reveal how it moves within an infected red blood cell. Using cryo-electron microscopy to visualise the assembly in fine detail, Schureck et al. showed that the three proteins bind tightly to each other over large areas using multiple anchor points. As the three proteins are produced, they assemble into a complex that remains dissolved and free of parasite membranes until the proteins have been delivered to their target red blood cells. Some hours after delivery, specific sections of the RhopH complex are inserted into the red blood cell membrane to produce pores that allow them to take up nutrients and to grow. The study of Schureck et al. provides important new insights into how the RhopH complex serves multiple roles during Plasmodium infection of human red blood cells. The findings provide a framework for the development of effective antimalarial treatments that target RhopH proteins to block red blood cell invasion and nutrient uptake.

Background Several studies have examined the drug–drug interaction patterns in different patient populations and treatment settings; however, there is a need, particularly in the field of oncology and radiotherapy, for evaluating methods targeted towards preventing potential drug–drug interactions. One of the measures proposed is identifying potential interactions using computer programs and their evaluation by pharmacologists or clinical pharmacists, thereby providing clinically relevant information to the treating physician regarding the required prescription changes. Objective To determine the prevalence of potential drug–drug interactions in patients receiving chemoradiotherapy and assess the usefulness of expert team recommendations in minimizing interactions. Setting Patients admitted to the radiotherapy and oncology ward of a tertiary care teaching hospital in Karnataka, India. Method We conducted a prospective, cross-sectional study of prescriptions written for patients receiving chemoradiotherapy. Prescriptions containing two or more drugs, at least one of the drugs being an anticancer drug, were analyzed. They were screened for potential drug–drug interactions using the Lexicomp® drug interaction software. The interactions were classified as X, drug combination to be avoided; D, modification of therapy to be considered; and C, therapy to be monitored, as per the Lexicomp criteria. Main outcome measure The number of drug–drug interactions detected that were accepted by the treating radio-oncologist as requiring prescription change before and after the prescription review by an expert team. Results Two hundred twenty-three prescriptions were screened for the presence of drug–drug interactions; 106 prescriptions (47.53%) containing 620 drugs and 211 drug–drug interactions were identified. Of the 211 interactions identified, 6.64% (14/211), 18.48% (39/211), and 74.88% (158/211) drug–drug interactions belonged to category X, D, and C, respectively. Twenty-seven (50.94%) of the 53 category X and D interactions identified were accepted the oncologist as requiring a change in the prescription; an additional 13 (24.53%) interactions were identified as significant by the expert team, and 11 (84.62%) of these were accepted by the oncologist. Conclusion A system of alerting the treating physician to a potential drug–drug interaction leads to avoidance of prescription of the interacting drug combination, and the assistance by an expert team adds significantly to avoidance of clinically relevant drug interactions.

Non-point source (NPS) pollution is an important problem that has been threatening freshwater resources throughout the world. Best Management Practices (BMPs) can reduce NPS pollution delivery to receiving waters. For economic reasons, BMPs should be placed at critical source areas (CSAs), which are the areas contributing most of the NPS pollution. The CSAs are the areas in a watershed where source coincides with transport factors, such as runoff, erosion, subsurface flow, and channel processes. Methods ranging from simple index-based to detailed hydrologic and water quality (HWQ) models are being used to identify CSAs. However, application of these methods for Canadian watersheds remains challenging due to the diversified hydrological conditions, which are not fully incorporated into most existing methods. The aim of this work is to review potential methods and challenges in identifying CSAs under Canadian conditions. As such, this study: (a) reviews different methods for identifying CSAs; (b) discusses challenges and the current state of CSA identification; and (c) highlights future research directions to address limitations of currently available methods. It appears that applications of both simple index-based methods and detailed HWQ models to determine CSAs are limited in Canadian conditions. As no single method/model is perfect, it is recommended to develop a ‘Toolbox’ that can host a variety of methods to identify CSAs so as to allow flexibility to the end users on the choice of the methods.

In rural Alaska, there are nearly 180 villages consuming about 374,000 MWh of electrical energy annually from individual diesel generators. A similar amount of fuel energy is dissipated into the atmosphere from diesel exhaust. Due to the isolation and small populations of the villages, the costs of fuels, components, and maintenance are extremely high and one of the policies in management is to minimize the possibilities of power outrage and the frequency of maintenance. Also due to the potential of corrosion and soot accumulation in exhaust heat recovery systems, exhaust heat recovery has long been avoided. Recently, the surge in fuel prices, the new regulation requiring ultra low sulfur diesel, and the desire to reduce green house gas has led to exhaust heat recovery being reconsidered for improving the energy efficiency of rural Alaskan diesel power plants. This report discusses the selection of different exhaust heat recovery applications to the villages, the design of an experimental system that simulates different space heating methods used in villages, system fabrication, instrumentation, system performance, feasibility and economic analysis. Performance presented includes the effect of the heat recovery system on engine performance, heat recovery effectiveness, measured soot accumulation and the effect of fouling on heat recovery effectiveness, and the estimated maintenance requirement.